Neural Network for Estimate of Organization’s Requirements for Highly Skilled Personnel

This article presents the results of research the needs companies for workers in regions of the Russian Federation, which is based on the use of neural network. There are discrepancy between the actual demand for highly skilled personnel and programs higher education. This situation could have a neg...

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Main Authors: Mikhail Valeryevich Zaboev, Maria Petrovna Mazyarkina
Format: Article
Language:English
Published: North-West institute of management of the Russian Presidential Academy of National Economy and Public Administration 2018-04-01
Series:Управленческое консультирование
Subjects:
Online Access:https://www.acjournal.ru/jour/article/view/388
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spelling doaj-bcd963de589a4f40b881ab2a1cc988112021-09-10T11:50:29ZengNorth-West institute of management of the Russian Presidential Academy of National Economy and Public Administration Управленческое консультирование1726-11391816-85902018-04-01086975388Neural Network for Estimate of Organization’s Requirements for Highly Skilled PersonnelMikhail Valeryevich Zaboev0Maria Petrovna Mazyarkina1Saint-Petersburg State UniversitySaint-Petersburg State UniversityThis article presents the results of research the needs companies for workers in regions of the Russian Federation, which is based on the use of neural network. There are discrepancy between the actual demand for highly skilled personnel and programs higher education. This situation could have a negative impact on the development of the regions. The result of the study is forecast the demand for workers for the mining industry in several regions of the country and the proposal to use this method to formation of programs in higher education.https://www.acjournal.ru/jour/article/view/388higher educationregionslabor marketneural networkself-organizing kohonen maps
collection DOAJ
language English
format Article
sources DOAJ
author Mikhail Valeryevich Zaboev
Maria Petrovna Mazyarkina
spellingShingle Mikhail Valeryevich Zaboev
Maria Petrovna Mazyarkina
Neural Network for Estimate of Organization’s Requirements for Highly Skilled Personnel
Управленческое консультирование
higher education
regions
labor market
neural network
self-organizing kohonen maps
author_facet Mikhail Valeryevich Zaboev
Maria Petrovna Mazyarkina
author_sort Mikhail Valeryevich Zaboev
title Neural Network for Estimate of Organization’s Requirements for Highly Skilled Personnel
title_short Neural Network for Estimate of Organization’s Requirements for Highly Skilled Personnel
title_full Neural Network for Estimate of Organization’s Requirements for Highly Skilled Personnel
title_fullStr Neural Network for Estimate of Organization’s Requirements for Highly Skilled Personnel
title_full_unstemmed Neural Network for Estimate of Organization’s Requirements for Highly Skilled Personnel
title_sort neural network for estimate of organization’s requirements for highly skilled personnel
publisher North-West institute of management of the Russian Presidential Academy of National Economy and Public Administration
series Управленческое консультирование
issn 1726-1139
1816-8590
publishDate 2018-04-01
description This article presents the results of research the needs companies for workers in regions of the Russian Federation, which is based on the use of neural network. There are discrepancy between the actual demand for highly skilled personnel and programs higher education. This situation could have a negative impact on the development of the regions. The result of the study is forecast the demand for workers for the mining industry in several regions of the country and the proposal to use this method to formation of programs in higher education.
topic higher education
regions
labor market
neural network
self-organizing kohonen maps
url https://www.acjournal.ru/jour/article/view/388
work_keys_str_mv AT mikhailvaleryevichzaboev neuralnetworkforestimateoforganizationsrequirementsforhighlyskilledpersonnel
AT mariapetrovnamazyarkina neuralnetworkforestimateoforganizationsrequirementsforhighlyskilledpersonnel
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